Transcriptional profiling unveils molecular subgroups of adaptive and maladaptive right ventricular remodeling in pulmonary hypertension.

Right ventricular (RV) function is critical to prognosis in all forms of pulmonary hypertension. Here we perform molecular phenotyping of RV remodeling by transcriptome analysis of RV tissue obtained from 40 individuals, and two animal models of RV dysfunction of both sexes. Our unsupervised clustering analysis identified 'early' and 'late' subgroups within compensated and decompensated states, characterized by the expression of distinct signaling pathways, while fatty acid metabolism and estrogen response appeared to underlie sex-specific differences in RV adaptation.

The remission status of AML patients after allo-HCT is associated with a distinct single-cell bone marrow T-cell signature.

Acute myeloid leukemia (AML) is a hematologic malignancy for which allogeneic hematopoietic cell transplantation (allo-HCT) often remains the only curative therapeutic approach. However, incapability of T cells to recognize and eliminate residual leukemia stem cells might lead to an insufficient graft-versus-leukemia (GVL) effect and relapse. Here, we performed single-cell RNA-sequencing (scRNA-seq) on bone marrow (BM) T lymphocytes and CD34+ cells of 6 patients with AML 100 days after allo-HCT to identify T-cell signatures associated with either imminent relapse (REL) or durable complete remission (CR).

GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks.

Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN).

Pan-cancer analysis of microRNA expression profiles highlights microRNAs enriched in normal body cells as effective suppressors of multiple tumor types: A study based on TCGA database.

Background: MicroRNAs (miRNAs) are frequently deregulated in various types of cancer. While antisense oligonucleotides are used to block oncomiRs, delivery of tumour-suppressive miRNAs holds great potential as a potent anti-cancer strategy. Here, we aim to determine, and functionally analyse, miRNAs that are lowly expressed in various types of tumour but abundantly expressed in multiple normal tissues.

Cell Identity Codes: Understanding Cell Identity from Gene Expression Profiles using Deep Neural Networks.

Understanding cell identity is an important task in many biomedical areas. Expression patterns of specific marker genes have been used to characterize some limited cell types, but exclusive markers are not available for many cell types. A second approach is to use machine learning to discriminate cell types based on the whole gene expression profiles (GEPs).